NodeConvolution Layer

Other

This node adds a Convolutional layer to the Deep Learning Model supplied by the input port. The layer performs convolution of the inputs (usually images) using a user defined number of convolution kernels.

Input ports

  1. Deep Learning Model Type: DL4J Model
    The model which will be extended by this layer.

Output ports

  1. Deep Learning Model Type: DL4J Model
    The model from the input port additionally containing this layer.

  1. Classifying handwritten digits using KNIME, DL4J and a LeNet variant

    deep learning GPU image classification digit recognition Le Net
    The workflow downloads, uncompresses and preprocesses the orignal MNIST dataset from: http://yann.lecun.com/exdb/mnist/ …
    aajaradata > 01_Using_DeepLearning4J_to_classify_MNIST_Digits

  2. Example of a simple Convolutional Network

    deeplearning machine learning classification neural networks convolutional
    This workflow shows how to create a simple convolutional network and use it for image classification.
    shima0011 > 04_Analytics > 14_Deep_Learning > 01_DL4J > 05_Network_Example_Of_A_Simple_Convolutional_Net

  3. Classifying handwritten digits using KNIME, DL4J and a LeNet variant

    deep learning GPU image classification digit recognition Le Net
    The workflow downloads, uncompresses and preprocesses the orignal MNIST dataset from: http://yann.lecun.com/exdb/mnist/ …
    aajaradata > 001_Using_DeepLearning4J_to_classify_MNIST_Digits

  4. Basic Concepts of Deeplearning4J Integration

    deeplearning machine learning neural networks
    This workflow shows basic concepts of the KNIME Deeplearning4J Integration.
    aajaradata > 01_Basic_Concepts_Of_Deeplearning4J_Integration

  5. Simple Anomaly Detection Using a Convolutional Network

    deeplearning machine learning anomaly detection neural networks convolutional
    This workflow shows how to do anomaly detection of the MNIST dataset using a convolutional network.
    knime > Examples > 04_Analytics > 14_Deep_Learning > 01_DL4J > 09_Simple_Anomaly_Detection_Using_A_Convolutional_Net

  6. Basic Concepts of Deeplearning4J Integration

    deeplearning machine learning neural networks
    This workflow shows basic concepts of the KNIME Deeplearning4J Integration.
    knime > Examples > 04_Analytics > 14_Deep_Learning > 01_DL4J > 01_Basic_Concepts_Of_Deeplearning4J_Integration

  7. Font Detection Using A Convolutional Net

    deeplearning machine learning classification neural networks convolutional
    This workflow shows an example of how to detect the fonts of letters using a convolutional network.
    knime > Examples > 04_Analytics > 14_Deep_Learning > 01_DL4J > 12_Font_Detection_Using_A_Convolutional_Net

  8. Example of a simple Convolutional Network

    deeplearning machine learning classification neural networks convolutional
    This workflow shows how to create a simple convolutional network and use it for image classification.
    knime > Examples > 04_Analytics > 14_Deep_Learning > 01_DL4J > 05_Network_Example_Of_A_Simple_Convolutional_Net

  9. Font Detection Using A Convolutional Net

    deeplearning machine learning classification neural networks convolutional
    This workflow shows an example of how to detect the fonts of letters using a convolutional network.
    shima0011 > 04_Analytics > 14_Deep_Learning > 01_DL4J > 12_Font_Detection_Using_A_Convolutional_Net

  10. Celebrity Recognition Using AlexNet

    deeplearning machine learning classification neural networks convolutional AlexNet
    This workflow shows an example of image classification of celebrity faces using AlexNet.
    knime > Examples > 04_Analytics > 14_Deep_Learning > 01_DL4J > 13_Celebrity_Detection_Using_Alex_Net